Case study 03
Analytics engineering · Self-service BI
Trusted KPI & Reporting System
A reusable analytics-engineering concept for turning inconsistent reporting logic into governed metrics, tested SQL models, and a self-service dashboard.
- SQL
- Metric design
- Data tests
- Documentation
- Power BI
- 1
- shared metric layer
- 3
- validation levels
- 0
- hidden definitions
01 · Business question
What needed to change?
When teams calculate the same KPI differently, dashboards become reconciliation tools instead of decision tools. This concept demonstrates how metric ownership, reusable transformations, testing, and documentation can become one coherent reporting product.
02 · Approach
From ambiguity to a system.
- 01
Start with the business decision and define each KPI in plain language before writing SQL.
- 02
Create reusable modeled tables at an explicit grain with documented dimensions and filters.
- 03
Add source, transformation, and business-rule tests to catch different classes of failure.
- 04
Publish a lightweight metric registry covering definition, owner, cadence, and known caveats.
- 05
Build the dashboard from the governed layer and preserve drill paths back to validated detail.
03 · Analytical flow
A repeatable path from question to action.
- 01Business question
- 02Metric contract
- 03SQL models
- 04Automated tests
- 05Self-service BI
04 · Outcome
One metric language shared across analysis, reporting, and business reviews.
- Makes analytical logic visible and reviewable before it reaches an executive dashboard.
- Separates reusable metric logic from presentation-specific calculations.
- Creates a clear path for extending the project with orchestration, lineage, and alerting.
Reflection
“This case study is intentionally a living portfolio build. Its success will be measured by reproducibility, clarity, and trust—not by the number of charts it contains.”